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UK cross-sectional equity data: The case for robust investability filters

Author

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  • Francesco Rossi

    (UCD School of Business, University College Dublin, Blackrock, Co. Dublin, Ireland)

Abstract

We propose a novel approach to cross-sectional equities sample selection, derived from best market practice in index construction and focused on investability. Using the UK market as a template, we first demonstrate how the popular Datastream dataset is plagued by data deficiencies that would surely invalidate statistical inferences, and that are not addressed by commonly used filters. We show the benefits and need for a supplementary data source. We then develop robust investability filters to ensure statistical results from cross-sectional analysis are economically meaningful, an issue overlooked by most studies on cross-sectional equity risk pricing.

Suggested Citation

  • Francesco Rossi, 2012. "UK cross-sectional equity data: The case for robust investability filters," European Economic Letters, European Economics Letters Group, vol. 1(1), pages 6-13.
    • Handle: RePEc:ris:eueclt:0002
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    Cited by:

    1. Stijn Claessens & Hui Tong & Igor Zuccardi, 2015. "Saving the Euro: Mitigating Financial or Trade Spillovers?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(7), pages 1369-1402, October.

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    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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